A Data Consistency Insurance Method for Smart Contract

As one of the major threats to the current DeFi(Decentralized Finance)ecosystem,reentrant attack induces data inconsistency of the victim smart contract,enabling attackers to steal on-chain assets from DeFi projects,which could terribly do harm to the confidence of the blockchain investors.However,protecting DeFi projects from the reentrant attack is very difficult,since generating a call loop within the highly automatic DeFi ecosystem could be very practicable.Existing researchers mainly focus on the detection of the reentrant vulnerabilities in the code testing,and no method could promise the non-existent of reentrant vulnerabilities.In this paper,we introduce the database lock mechanism to isolate the correlated smart contract states from other operations in the same contract,so that we can prevent the attackers from abusing the inconsistent smart contract state.Compared to the existing resolutions of front-running,code audit,andmodifier,our method guarantees protection resultswith better flexibility.And we further evaluate our method on a number of de facto reentrant attacks observed from Etherscan.The results prove that our method could efficiently prevent the reentrant attack with less running cost.

Reducing nitrogen application with dense planting increases nitrogen use efficiency by maintaining root growth in a double-rice cropping system

Rational nitrogen(N) application can greatly increase rice(Oryza sativa L.) yield. However, excessive N input can lead not only to low N use efficiency(NUE) but also to severe environmental pollution.Reducing N application rate with a higher planting density(RNHD) is recommended to maintain rice yield and improve NUE. The effects of RNHD on fertilizer N fate and rice root growth traits remain unclear. We accordingly conducted a two-year field experiment to investigate the influence of RNHD on rice yield, fertilizer 15N fate, and root growth in a double-rice cropping system in China. In comparison with the conventional practice of high N application with sparse planting, RNHD resulted in similar yield and biomass production as well as plant N uptake. RNHD increased agronomic NUEs by 23.3%–31.9%(P < 0.05) and N recovery efficiency by 17.4%–24.1%(P < 0.05). RNHD increased fertilizer 15N recovery rate by 14.5%–34.7%(P < 0.05), but reduced15 N retention rate by 9.2%–12.0%(P < 0.05). Although a reduced N rate led to significantly reduced root length, surface area, volume, and biomass, these root traits were significantly increased by higher planting density. RNHD did not affect these root morphological traits and reduced activities of nitrate reductase(NR) and glutamine synthetase(GS) only at tillering stage. Plant N uptake was significantly positively correlated with these root traits, but not correlated with NR and GS activities. Together, these findings show that reducing N application with dense planting can lead to high plant N uptake by maintaining rice root growth and thus increase NUE.

A Trusted NUMFabric Algorithm for Congestion Price Calculation at the Internet-of-Things Datacenter

The important issues of network TCP congestion control are how to compute the link price according to the link status and regulate the data sending rate based on link congestion pricing feedback information.However,it is difficult to predict the congestion state of the link-end accurately at the source.In this paper,we presented an improved NUMFabric algorithm for calculating the overall congestion price.In the proposed scheme,the whole network structure had been obtained by the central control server in the Software Defined Network,and a kind of dual-hierarchy algorithm for calculating overall network congestion price had been demonstrated.In this scheme,the first hierarchy algorithm was set up in a central control server like Opendaylight and the guiding parameter B is obtained based on the intelligent data of global link state information.Based on the historical data,the congestion state of the network and the guiding parameter B is accurately predicted by the machine learning algorithm.The second hierarchy algorithm was installed in the Openflow link and the link price was calculated based on guiding parameter B given by the first algorithm.We evaluate this evolved NUMFabric algorithm in NS3,which demonstrated that the proposed NUMFabric algorithm could efficiently increase the link bandwidth utilization of cloud computing IoT datacenters.

Metal oxide mesocrystals and mesoporous single crystals:synthesis,properties and applications in solar energy conversion

Metal oxide mesocrystals(MCs)and mesoporous single crystals(MSCs)exhibit superior carrier transport ability,high specific surface area,shortened photo-carrier diffusion lengths to interfaces and enhanced absorbance of the incident sunlight.These advanced features make metal oxide MCs and MSCs be a promising candidate material in photocatalysis,photoelectrocatalysis,dye sensitized solar cells(DSSCs)and perovskite solar cells(PSCs).Recently,remarkable advances of applying metal oxide MCs and MSCs in these areas have been achieved.Therefore,it is extremely important to deeply understand the influence of the unique properties of metal oxide MCs and MSCs on solar energy conversion systems.Herein,we presented a brief introduction on the synthesis and carrier transfer behavior of metal oxide MCs and MSCs.Then,the rational structure design and modification of metal oxide MCs and MSCs for photocatalysis,photoelectrocatalysis,DSSCs and PSCs are systematically discussed.Finally,the perspectives on extending the application of metal oxide MCs and MSCs are addressed.